Design of an Automatic PC Assembly Recommendation System Based on Gaming or Multitasking Needs According to Budget Using Natural Language Processing
Perancangan Sistem Rekomendasi Rakit PC Otomatis Berdasarkan Kebutuhan Gaming atau Multitasking Sesuai Budget Menggunakan Natural Language Processing
DOI:
https://doi.org/10.21070/ups.11270Keywords:
Recommendation System, PC Assembly, Natural Language Processing, K-Nearest Neighbors, React JS, FlaskAbstract
The demand for Personal Computers (PCs) tailored to users' specific requirements continues to increase. Selecting appropriate PC components is often a complex challenge for novice users due to limited technical knowledge regarding hardware compatibility and price variations. This can lead to cost inefficiency and incompatible hardware configurations. This study aims to design an automatic PC assembly recommendation system that processes users' requirements expressed in natural language. The proposed method employs Natural Language Processing (NLP) based on a keyword dictionary to extract specific user needs and budget constraints from text input. Furthermore, the K-Nearest Neighbors (KNN) algorithm is applied to identify the most relevant components, combined with Constraint-Based Filtering to ensure technical compatibility among components and compliance with the user's budget. The system is developed using a React JS and a Flask . Experimental results demonstrate that the proposed system successfully generates optimal, compatible, and user-preference-based, achieving an accuracy of 70%.
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